Electromagnetic + Hadronic Sampling Calorimeter Shower Images

We include multiple hdf5 files: The files 'piplus_1.hdf5' and 'piplus_2.hdf5' each contains 100,000 calorimeter showers originating from incoming charged pions with incident energies uniformly distributed in the range [1,100] GeV. The file 'piplus_1.hdf5' was used to train our models. The second file 'piplus_2.hdf5' was used in evaluation of generation performance. The file 'piplus_log.hdf5' contains 100,000 calorimeter showers originating from incoming charged pions with incident energies log-uniformly distributed in the range [1,100] GeV. The files with names 'piplus_{E_true}.hdf5' each contain 100,000 calorimeter showers originating from incoming charged pions with fixed incident energy at E_true = {10, 20, 30, 40, 50, 60, 70, 80, 90} GeV. These files were used for evaluation of calibration performance. Each file has the following structure: energy Dataset {100000, 1} layer_0 Dataset {100000, 3, 96} layer_1 Dataset {100000, 12, 12} layer_2 Dataset {100000, 12, 6} layer_3 Dataset {100000, 3, 96} layer_4 Dataset {100000, 12, 12} layer_5 Dataset {100000, 12, 6} overflow Dataset {100000, 6} The sampling calorimeter we built is segmented longitudinally into six layers with different depths and granularities. In units of mm, the six layers have the following (eta, phi, z) dimensions:Layer 0: (5, 160, 90) | Layer 1: (40, 40, 347) | Layer 2: (80, 40, 43) | Layer 3: (20.83, 666.67, 375) | Layer 4: (166.67, 166.67, 667) | Layer 5: (333.33, 166.67, 958)本数据集包含若干HDF5（Hierarchical Data Format 5）格式文件： `piplus_1.hdf5`与`piplus_2.hdf5`两个文件各存储100000条由入射带电π介子产生的量能器簇射数据，其入射能量在[1, 100]吉电子伏特（GeV）范围内均匀分布。其中`piplus_1.hdf5`用于模型训练，`piplus_2.hdf5`则用于生成性能评估。 `piplus_log.hdf5`文件包含100000条由入射带电π介子产生的量能器簇射数据，其入射能量在[1, 100] GeV范围内呈对数均匀分布。 命名格式为`piplus_{E_true}.hdf5`的文件各存储100000条由入射带电π介子产生的量能器簇射数据，其入射能量固定为E_true = {10, 20, 30, 40, 50, 60, 70, 80, 90} GeV。此类文件用于校准性能评估。 每个文件均包含如下结构的数据集： energy：形状为{100000, 1}的数据集 layer_0：形状为{100000, 3, 96}的数据集 layer_1：形状为{100000, 12, 12}的数据集 layer_2：形状为{100000, 12, 6}的数据集 layer_3：形状为{100000, 3, 96}的数据集 layer_4：形状为{100000, 12, 12}的数据集 layer_5：形状为{100000, 12, 6}的数据集 overflow：形状为{100000, 6}的数据集 本研究搭建的取样型量能器沿纵向被划分为六层，各层具有不同的深度与单元粒度。六层的（η, φ, z）尺寸（单位：毫米）如下： 第0层：(5, 160, 90) | 第1层：(40, 40, 347) | 第2层：(80, 40, 43) | 第3层：(20.83, 666.67, 375) | 第4层：(166.67, 166.67, 667) | 第5层：(333.33, 166.67, 958)